Qwen 3.5 122B MoE OC on a single 3090 at 35 t/s — full local stack breakdown

I know, it’s not the 27B, I’m actually replacing that model after 2 months because MTP just flipped the math for me. Rough draft from my 35B written using a LoRa adapter with my register. TLDR: stuff bigger models on your hardware, better claw. Running a fully local inference stack on a single desktop. No cloud, no API costs. Sharing because this took a lot of iteration to get right and the MoE offload numbers might save someone else time. I write commercial automation workflows and develop games as a solo dev. Hardware AMD 9900X, 192GB DDR5-5200, two 3090s (Ti + standard), no NVLink. The RAM is the secret weapon Card 1 — (the worker) Qwen3.5-122B-A10B, Unsloth IQ3\_S MTP GGUF, 204K context. 75% of expert layers offloaded to CPU via surgical -ot. Running on ik\_llama.cpp (not stock) — this is the key finding. Stock llama.cpp MTP on offloaded MoE barely helps (+4%). ik’s fused MoE ops batch the expert reads for speculated tokens, turning MTP into an actual +20% gain. 35 t/s decode on a 122B model from a single 3090. Card 2 — (the reasoner) Qwen3.6-35B-A3B Q4\_K\_XL with MTP. 262K context. 135 t/s. This is the fast-response model for creative work and conversation. CPU dreamers Three llama.cpp instances on CPU only (no GPU contention): Dialectic (35B heretic Q8), Scribe-Logos (Gemma4 19B), Moonshot (Gemma4 2B). \~19GB RAM total. Background processing, verification, second opinions. The harness OpenClaw ties it together. OpenClaw’s embedded runner handles failover — if local dies it can fall through to cloud, which doesn’t happen for me yet. The ik\_llama.cpp finding This is the thing I’d highlight for anyone running MoE with expert offload. Stock llama.cpp’s MTP evaluates each speculated token’s experts sequentially through DDR5. On reasoning content it actually regresses — the draft overhead costs more than the acceptance saves. ik’s fused MoE ops fix this entirely. Same acceptance rate, 5x the effective speedup. If you’re offloading experts to RAM on any MoE model, try the ik fork before giving up on MTP. Total cost: hardware was \~$1600 for the ram and $1600 for the 2x3090s and $400 for everything else. Running cost is electricity.